Welding quality evaluation using residual based reference temperature distribution model and fuzzy reasoning
Y. Laib dit leksir1,2, S. Bouhouche2, M. S. Boucherit1, M. Mansour 3
1 Laboratoire de commande des processus - ENP, 10 Avenue hacene badi el harrach, Algiers, Algeria
2 Iron and steel applied research unit – CSC, BP 196, Annaba, 23000, Algeria
3 Faculté electronique et informatique, Université des sciences et de la technologie USTHB, Algérie
Abstract
This paper introduces a method for Submerged Arc Welding (SAW) quality evaluation, which combines model identification
and fuzzy sets methods. To account for SAW quality variations, the proposed approach is based on an optimal reference Gauss distribution temperature along of the welding line in order to take into account the eventual process changes. Fuzzy analysis is then applied to the generated residual data to give an evaluation of the welding condition. This approach is applied to welding process for constructing a complementary condition monitoring system which permits a non-destructive online and real-time quality evaluation. The temperature measurement is carried out using an infrared camera. Simulation results based on the measured surface temperature and generated residual data show that the new approach is easily implementable, efficient and gives good evaluation online.
Keywords
Heat Affected Zone of Welding Process, Infrared temperature measurement, Gauss distribution model, Residual generation, intelligent modeling, Fuzzy reasoning, Quality evaluation.
